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Record W2987952774 · doi:10.1002/jcb.29515

Comparison of the roles of estrogens and androgens in breast cancer and prostate cancer

2019· review· en· W2987952774 on OpenAlexafffund
Wenjing Liu, Gang Zhao, Chen‐Yan Zhang, Changqing Yang, Xiangbin Zeng, Jin Li, Kun Zhu, Shi‐Qi Zhao, Hui‐Meng Lu, Da‐Chuan Yin, Sheng‐Xiang Lin

Bibliographic record

VenueJournal of Cellular Biochemistry · 2019
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health ResearchChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsProstate cancerCancerBreast cancerProstateOncologyInternal medicineMedicineBiologyGynecology

Abstract

fetched live from OpenAlex

Breast cancer (BC) and prostate cancer (PC) are the second most common malignant tumors in women and men in western countries, respectively. The risks of death are 14% for BC and 9% for PC. Abnormal estrogen and androgen levels are related to carcinogenesis of the breast and prostate. Estradiol stimulates cancer development in BC. The effect of estrogen on PC is concentration-dependent, and estrogen can regulate androgen production, further affecting PC. Estrogen can also increase the risk of androgen-induced PC. Androgen has dual effects on BC via different metabolic pathways, and the role of the androgen receptor (AR) in BC also depends on cell subtype and downstream target genes. Androgen and AR can stimulate both primary PC and castration-resistant PC. Understanding the mechanisms of the effects of estrogen and androgen on BC and PC may help us to improve curative BC and PC treatment strategies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.623
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.382
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2019
Admission routes2
Has abstractyes

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